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Teaching computing for complex problems in civil engineering and geosciences using big data and machine learning: synergizing four different computing paradigms and four different management domains

Overview of attention for article published in Journal of Big Data, May 2023
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Title
Teaching computing for complex problems in civil engineering and geosciences using big data and machine learning: synergizing four different computing paradigms and four different management domains
Published in
Journal of Big Data, May 2023
DOI 10.1186/s40537-023-00730-7
Authors

Zoran Babović, Branislav Bajat, Dusan Barac, Vesna Bengin, Vladan Đokić, Filip Đorđević, Dražen Drašković, Nenad Filipović, Stephan French, Borko Furht, Marija Ilić, Ayhan Irfanoglu, Aleksandar Kartelj, Milan Kilibarda, Gerhard Klimeck, Nenad Korolija, Miloš Kotlar, Miloš Kovačević, Vladan Kuzmanović, Jean-Marie Lehn, Dejan Madić, Marko Marinković, Miodrag Mateljević, Avi Mendelson, Fedor Mesinger, Gradimir Milovanović, Veljko Milutinović, Nenad Mitić, Aleksandar Nešković, Nataša Nešković, Boško Nikolić, Konstantin Novoselov, Arun Prakash, Jelica Protić, Ivan Ratković, Diego Rios, Dan Shechtman, Zoran Stojadinović, Andrey Ustyuzhanin, Stan Zak

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 5 9%
Researcher 3 6%
Lecturer 3 6%
Student > Ph. D. Student 3 6%
Student > Bachelor 2 4%
Other 8 15%
Unknown 30 56%
Readers by discipline Count As %
Unspecified 5 9%
Business, Management and Accounting 4 7%
Computer Science 3 6%
Engineering 3 6%
Arts and Humanities 2 4%
Other 5 9%
Unknown 32 59%